There has been a great deal of study of the principles of edge detection and contrast perception both in the human visual system and for the purpose of enhancing machine vision. While there has been a great deal of work in these areas, little work has been addressed to the problem of distinguishing illumination variations (e.g. shadows) from reflectance variations. This difficulty in distinguishing illumination variations from reflectance variations results in the difficulty of recognizing object features as distinguished from illumination variations both for the human visual system, and in machine vision systems. Nevertheless, the human visual system is remarkably successful in separating contrast variation due to variation in illumination from reflectance magnitude changes due to the physical configuration of the scene being viewed.
Current machine vision systems exhibit undesired sensitivity to varying illumination. For current machine vision systems to be useful, the illumination of the viewed scene must be closely controlled to eliminate shadows and to make the desired features more prominent than other parts of the scene. Accordingly, machine vision systems are not particularly robust against varying illumination conditions such as encountered in normal outdoor scenes or in any location where illumination is not fully controlled. For this reason, current applications of industrial vision systems utilize closely controlled lighting. However, it has been long desirable to utilize machine vision systems in environments where the lighting is not well controlled. Current vision systems are unable to distinguish objects edges from shadows and thus are not generally useful in such an environment. A need in the art exists for a vision system which is capable of distinguishing shadows and abrupt object edges so that the system may be utilized without the need to closely control lighting. Such a system would be useful in a variety of areas including, but not limited to, the control of robotic manipulators, intrusion detection alarms and mechanical sorters.